html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/4541#issuecomment-717625573,https://api.github.com/repos/pydata/xarray/issues/4541,717625573,MDEyOklzc3VlQ29tbWVudDcxNzYyNTU3Mw==,14314623,2020-10-28T00:45:31Z,2020-10-28T00:45:31Z,CONTRIBUTOR,"> Another option would be to put the check in a `.map_blocks` call for dask arrays. This would only run and raise at compute time.

Uh that sounds great actually. Same functionality, no triggered computation, and no intervention needed from the user. Should I try to implement this?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,729980097
https://github.com/pydata/xarray/issues/4541#issuecomment-717266102,https://api.github.com/repos/pydata/xarray/issues/4541,717266102,MDEyOklzc3VlQ29tbWVudDcxNzI2NjEwMg==,14314623,2020-10-27T14:03:34Z,2020-10-27T14:03:34Z,CONTRIBUTOR,"Thanks @mathause , I was wondering how much of a performance trade off `.fillna(0)` is on a dask array with no nans, compared to the check.
 
I favor this, since it allows slicing before the calculation is triggered: I have a current situation where I do a bunch of operations on a large multi-model dataset. The weights are time and member dependent and I am trying to save each member separately. Having the calculation triggered for the full dataset is problematic and `fillna(0)` avoids that (working with a hacked branch where I simply removed the check for nans)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,729980097
https://github.com/pydata/xarray/issues/4541#issuecomment-716974071,https://api.github.com/repos/pydata/xarray/issues/4541,716974071,MDEyOklzc3VlQ29tbWVudDcxNjk3NDA3MQ==,14314623,2020-10-27T04:33:04Z,2020-10-27T04:33:04Z,CONTRIBUTOR,Sounds good. I'll see if I can make some time to test and put up a PR this week.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,729980097
https://github.com/pydata/xarray/issues/4541#issuecomment-716930400,https://api.github.com/repos/pydata/xarray/issues/4541,716930400,MDEyOklzc3VlQ29tbWVudDcxNjkzMDQwMA==,14314623,2020-10-27T02:06:35Z,2020-10-27T02:06:35Z,CONTRIBUTOR,"What would happen in this case **if** a dask array with nans is passed? Would this somehow silently influence the results or would it not matter (in that case I wonder what the check was for).
If this could lead to undetected errors I would still consider a kwargs a safer alternative, especially for new users?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,729980097
https://github.com/pydata/xarray/issues/4541#issuecomment-716927242,https://api.github.com/repos/pydata/xarray/issues/4541,716927242,MDEyOklzc3VlQ29tbWVudDcxNjkyNzI0Mg==,14314623,2020-10-27T01:56:28Z,2020-10-27T01:56:28Z,CONTRIBUTOR,"Sorry if my initial issue was unclear.
So you favor not having a 'skip' kwarg to just internally skipping the call to `.any()` if `weights` is a dask array?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,729980097